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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Archives</journal-id>
<journal-title-group>
<journal-title>The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">ISPRS-Archives</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2194-9034</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/isprs-archives-L-4-W2-2026-245-2026</article-id>
<title-group>
<article-title>Evaluating High-Resolution Geospatial Data for Urban Microclimate Simulations: A Comparative Study Using Official Local and Open Global Datasets in Sofia</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Vitanova</surname>
<given-names>Lidia Lazarova</given-names>
<ext-link>https://orcid.org/0000-0003-1789-3901</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Fujiwara</surname>
<given-names>Kunihiko</given-names>
<ext-link>https://orcid.org/0000-0002-8044-8838</ext-link>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Karube</surname>
<given-names>Ryota</given-names>
<ext-link>https://orcid.org/0000-0002-1142-3768</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Shirinyan</surname>
<given-names>Evgeny</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Azegami</surname>
<given-names>Yasuhiko</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Doan</surname>
<given-names>Quang-Van</given-names>
<ext-link>https://orcid.org/0000-0002-2794-5309</ext-link>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Kusaka</surname>
<given-names>Hiroyuki</given-names>
<ext-link>https://orcid.org/0000-0002-0326-7179</ext-link>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Petrova-Antonova</surname>
<given-names>Dessislava</given-names>
<ext-link>https://orcid.org/0000-0002-9920-8877</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Ilieva</surname>
<given-names>Sylvia</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>GATE Institute, Sofia University “St. Kliment Ohridski”, Sofia, Bulgaria</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Research &amp; Development Institute, Takenaka Corporation, Japan</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>Graduate School of Science and Technology, University of Tsukuba, Japan</addr-line>
</aff>
<aff id="aff4">
<label>4</label>
<addr-line>Center for Computational Sciences, University of Tsukuba, Japan</addr-line>
</aff>
<pub-date pub-type="epub">
<day>28</day>
<month>09</month>
<year>2026</year>
</pub-date>
<volume>L-4/W2-2026</volume>
<fpage>245</fpage>
<lpage>252</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Lidia Lazarova Vitanova et al.</copyright-statement>
<copyright-year>2026</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/L-4-W2-2026/245/2026/isprs-archives-L-4-W2-2026-245-2026.html">This article is available from https://isprs-archives.copernicus.org/articles/L-4-W2-2026/245/2026/isprs-archives-L-4-W2-2026-245-2026.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/L-4-W2-2026/245/2026/isprs-archives-L-4-W2-2026-245-2026.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/L-4-W2-2026/245/2026/isprs-archives-L-4-W2-2026-245-2026.pdf</self-uri>
<abstract>
<p>Recent advances in digital technologies have enabled the development of urban tools that integrate geospatial data to support the analysis of complex urban systems and climate change. However, the reliability of such tools depends strongly on the availability and integration of high-quality geospatial data. This study evaluates the suitability of official local and open global geospatial data for high-resolution urban climate simulations through a comparative two-case approach: (1) using official local datasets (OLD) and (2) open global datasets (OGD) processed through ArcGIS Pro and VoxCity, respectively. Both datasets are incorporated into the City-LES model to simulate urban microclimate conditions. The Lozenets district in Sofia is selected as a representative case study. The simulation results from the City-LES model using the OLD and OGD datasets are compared and verified to assess the ability of local and global data to reproduce urban microclimate conditions. The results show that both OLD and OGD datasets effectively represent urban morphology and support microclimate simulations. While the simulation with the OLD provides detailed spatial resolution, the simulation with the OGD captures the overall urban structure, demonstrating complementary strengths. Differences in input data lead to variations in simulated microclimate conditions, particularly at finer spatial scales. The verified workflow demonstrates that official local and open global datasets complement each other in supporting scalable urban climate modelling, enabling urban heat assessment, climate adaptation planning, and evidence-based decision-making in data-scarce regions.</p>
</abstract>
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